- Accenture's report reveals European firms must accelerate AI adoption to reduce productivity gaps.
- European workers currently produce 76% of what their US counterparts do, highlighting technology underinvestment.
- Enhancing AI capabilities in large European companies could boost annual revenues by nearly €200 billion.
European companies need to intensify their AI scaling efforts to diminish a widening productivity gap and enhance competitiveness, according to a new report by Accenture (ACN, Financial). The study indicates that European workers produce only 76% as much as their American counterparts, a stark decrease from 30 years ago when productivity levels were similar. The persistent underinvestment in technology is cited as a significant factor.
Although the Draghi report has identified AI as a solution to Europe's productivity issues, Accenture highlights that more than half (56%) of large European firms have not scaled significant AI investments. The report suggests that if large (€1 billion+) companies improved their AI capabilities, annual business revenues could see an uptick of nearly €200 billion.
Mauro Macchi, CEO of Accenture in EMEA, stressed the urgency in addressing Europe's productivity gap amid rising geopolitical uncertainties. AI, he noted, is a key driver for economic reinvention and competitiveness. To fully capitalize on AI, European firms must invest in cloud technologies, modernize data infrastructure, and enhance workforce skills.
The study also points out the uneven adoption of AI across different sectors. While industries like automotive, aerospace, and defense are leading AI implementation, telecommunications and utilities lag behind. These differences pose a threat to regional competitiveness and sovereignty, especially when considering the vital role these sectors play in infrastructure.
Accenture's report recommends a coordinated industrial strategy to integrate AI capabilities across various industries and countries. This includes bridging the gap for smaller companies, fostering a sovereign AI ecosystem in Europe, and emphasizing AI literacy and workforce development. With 60% of European workers concerned about job displacement due to AI, and 36% feeling inadequately trained to use AI tools, the need for comprehensive training and support is clear.
Key challenges to AI scaling include establishing a robust data foundation, assembling multidisciplinary teams, managing security risks, and proving business value. To overcome these, companies should focus on data infrastructure, continuous talent development, secure digital systems, and identifying use cases with proven returns on investment.
